The traditional medicine licorice is the most widely consumed herbal product in the world. Although much research work on studying the changes in the active compounds of licorice has been reported, there are still many areas, such as the dynamic accumulation of secondary metabolites in licorice, that need to be further studied. In this study, the secondary metabolites from licorice under two different methods of stress were investigated by ultra-high-performance liquid chromatography coupled with hybrid linear ion trap–Orbitrap mass spectrometry (UHPLC-LTQ-Orbitrap-MS). A complex continuous coordination of flavonoids and triterpenoids in a network was modulated by different methods of stress during growth. The results showed that a total of 51 secondary metabolites were identified in licorice under ABA stress. The partial least squares–discriminate analysis (PLS-DA) revealed the distinction of obvious compounds among stress-specific districts relative to ABA stress. The targeted results showed that there were significant differences in the accumulation patterns of the deeply targeted 41 flavonoids and 10 triterpenoids compounds by PCA and PLS-DA analyses. To survey the effects of flavonoid and triterpenoid metabolism under ABA stress, we inspected the stress-specific metabolic changes. Our study testified that the majority of flavonoids and triterpenoids were elevated in licorice under ABA stress, while the signature metabolite affecting the dynamic accumulation of secondary metabolites was detected. Taken together, our results suggest that ABA-specific metabolite profiling dynamically changed in terms of the biosynthesis of flavonoids and triterpenoids, which may offer new trains of thought on the regular pattern of dynamic accumulation of secondary metabolites in licorice at the metabolite level. Our results also provide a reference for clinical applications and directional planting and licorice breeding.

Lonicerae japonicae flos, a common clinical Chinese medicine, is widely used in proprietary traditional Chinese medicine for the treatment of various conditions, such as fever, cough, and influenza. The microscopic features of honeysuckle pollen grains significantly correlate with their medicinal effects. In this study, deep learning using artificial intelligence was cross-combined with microscopic images of Chinese herbal medicines, and we proposed microscopic identification through an intelligent recognition method of honeysuckle pollen grains using microscopic images based on YOLO v5. The expandability of the microscopic feature recognition of different magnification models was verified based on different microscopic objectives. The honeysuckle pollen grains model based on YOLO v5 can quickly and accurately identify the microscopic images of pollen grains, which can provide a reference for the quality improvement and quality standardization of traditional Chinese herbs and has good application prospects.

The NAC family is among the most extensive sets of plant-exclusive transcription factors (TFs), which are crucial for various plant development and stress response processes. Although a growing number of studies have been carried out on the NAC family in different species, it has not been characterized in Glycyrrhiza uralensis. To thoroughly understand the effects of methyl jasmonate (MeJA) and sodium chloride (NaCl) inductions on NAC TFs and investigate the underlying regulatory mechanism of NAC TFs in response to MeJA and NaCl on the biosynthesis of metabolites, we used transcriptome sequencing combined with qRT‒PCR to explore differential gene expression. Comparative transcriptomic profiling by RNA sequencing (RNA-seq) revealed differentially expressed NAC TFs between MeJA/CK (Mock Control) and NaCl/CK. KEGG pathway analysis revealed that NAC TFs involved in starch and sucrose, carbohydrate, lipid, and amino acid metabolism, as well as terpenoid, polyketide, and flavonoid pathways, can regulate the MeJA- and NaCl-induced responses of G. uralensis. This research lays the groundwork for a thorough comprehension of the regulatory mechanism of NAC TFs in response to MeJA and NaCl induction and their involvement in the accumulation of secondary metabolites, which can provide a scientific basis for the cultivation of high-quality varieties of G. uralensis.

The structures of complexes of alditols where μ ₂ -bridge-relevant-deprotonations occur are described and the structural features of the complexes are discussed.

Background: Lonicerae japonicae flos (LJF), a traditional food and medicine with a history spanning thousands of years, undergoes drying as a critical processing step in modern applications after regular processing. While the by-products of this process are typically discarded as waste, the potential value of LJF condensate water (JYHC) remains largely unexplored. To address this gap and investigate its potential utilization, this study conducted widely targeted metabolome and volatile metabolomics profiling analyses of ‘JYHC’. Methods: This study analyzed the differential metabolites of ‘JYHC’ and dried Lonicerae japonicae flos (JYHG) based on widely targeted metabolomics using UPLC-MS/MS. Additionally, the metabolic differences between fresh Lonicerae japonicae flos (JYHX) and ‘JYHC’ based on GC-MS volatile metabolomics were comprehensively analyzed. Results: A total of 1651 secondary metabolites and 909 volatile metabolites were identified in this study. Among these, flavonoids and terpenoids were the predominant secondary metabolites, while esters and terpenoids dominated the volatile fraction. Further comparison of the ‘JYHC’ and ‘JYHG’ groups revealed that 58 differential metabolites with potential biological activities were significantly up-regulated, with the types being terpenoids, phenolic acids, and alkaloids, which included nootkatone, mandelic acid, sochlorogenic acid B, allantoin, etc. Notably, a total of 186 novel compounds were detected in ‘JYHC’ that had not been previously reported in LJF such as isoborneol, hinokitiol, agarospirol, 5-hydroxymethylfurfural, α-cadinol, etc. Conclusions: This study’s findings highlight the metabolic diversity of ‘JYHC’, offering new theoretical insights into the study of LJF and its by-products. Moreover, this research provides valuable evidence supporting the potential utilization of drying by-products from LJF processing, paving the way for further exploration of their pharmaceutical and industrial applications.

Background: This cross-sectional study aimed to investigate the relationships between gut microbiota compositional alterations and chronic metabolic disorders by analyzing taxonomic diversity, community structure, and species-level differences in individuals with hyperuricemia (HUA) and a history of being overweight. Our findings offer novel insights into microbiota-targeted therapeutic strategies for managing metabolic diseases. A total of 144 participants were recruited and divided into three diagnostic categories: healthy controls (HL, n = 29), hyperuricemia group (HU, n = 24), and overweight (OW, n = 91). Methods: Comprehensive phenotypic profiles and metagenomes were analyzed for fecal samples from the three groups. Results: Significant differences were observed in psychological states and microbial ecology between the metabolic disorder groups (HU and OW) and the control group (HL) (p < 0.05). Both the overweight individuals and those with HUA presented significant changes in gut microbial composition, with reduced α-diversity indices (Shannon index: HU vs HL Mann–Whitney U = 306; p = 0.462; OW vs HL Mann–Whitney U = 1008; p = 0.040; richness index: HU vs HL Mann–Whitney U = 307; p = 0.469; OW vs HL Mann–Whitney U = 1072; p = 0.092) compared to healthy individuals. Moreover, analysis of the linear discriminant analysis effect size (LEfSe) identified four discriminatory species in the HU group (Alistipes putredinis, Mediterraneibacter faecis, Streptococcus oralis, and Gemella sanguinis), and five in the OW group (Pantoea endophytica, Pantoea vagans, Phocaeicola coprophilus, Ruminococcus SGB4421, and Klebsiella oxytoca), representing potential biomarkers for the progression of chronic metabolic diseases. Conclusion: This study elucidates the characteristics of overweight individuals and those with HUA in terms of phenotypic features and gut microbiota, providing a theoretical reference for gut microbiota-targeted therapies and lifestyle interventions in chronic metabolic diseases.